{"id":165613,"date":"2026-02-19T20:02:02","date_gmt":"2026-02-19T19:02:02","guid":{"rendered":"https:\/\/liora.io\/en\/?p=165613"},"modified":"2026-02-19T20:02:03","modified_gmt":"2026-02-19T19:02:03","slug":"data-analyst-job-description","status":"publish","type":"post","link":"https:\/\/liora.io\/en\/data-analyst-job-description","title":{"rendered":"Data Analyst: Job Description, Duties, and Requirements"},"content":{"rendered":"<p><strong>With the advent of e-commerce and social networks, massive amounts of data have emerged. This is called Big Data. All this information has become crucial for companies to analyze competition, get feedback on their products\/services and attract customers. To manage and collect these astronomical amounts of data, companies use data analysts and data scientists. They are at the heart of digital and digital issues today. The employability rate in data science is very high. Data training is also in demand because the data analyst profession has become indispensable for companies to remain competitive.<\/strong><\/p><h2>What are the missions of the Data Analyst ?<\/h2>\nThe <strong><a href=\"\/en\/courses\/data-ai\/data-analyst\">data analyst<\/a><\/strong> collects data. Then it analyzes that data and makes it usable for the company. The data analyst explores all this data in order to find the most relevant ones. This is <b>Data Mining<\/b>. It must ensure the quality of the data and <b>update it regularly<\/b>. Like a consultant, he must, through his expertise, <b>solve problems encountered<\/b> by companies.\n<h2>What skills are required to be a good Data Aanlyst?<\/h2><figure class=\"wp-block-image size-large\" style=\"margin-top:var(--wp--preset--spacing--columns);margin-bottom:var(--wp--preset--spacing--columns)\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"572\" src=\"https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-1024x572.jpg\" alt=\"Four people in a meeting around a table, with a computer and notes, discussing a project in a bright office.\" class=\"wp-image-207691\" srcset=\"https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-56x56.jpg 56w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-115x64.jpg 115w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-150x150.jpg 150w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-210x117.jpg 210w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-300x167.jpg 300w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-410x270.jpg 410w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-440x246.jpg 440w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-448x448.jpg 448w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-587x510.jpg 587w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-768x429.jpg 768w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-785x438.jpg 785w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-1024x572.jpg 1024w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-1250x590.jpg 1250w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-1440x680.jpg 1440w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-1536x857.jpg 1536w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1-2048x1143.jpg 2048w, https:\/\/liora.io\/app\/uploads\/sites\/9\/2026\/02\/team-meeting-case-study-1.jpg 2560w\" sizes=\"(max-width: 1024px) 100vw, 1024px\"><\/figure>\nBecoming a data analyst requires <b>statistical learning<\/b>. Indeed, the role of the data analyst is similar to that of a translator. It must<b> translate abstract data<\/b> into statistical data that the company can use for its<b> marketing strategy<\/b> or to monitor its competitors. He must also be proficient in programming software such as <strong><a href=\"https:\/\/liora.io\/en\/python-the-most-popular-programming-language\">Python<\/a><\/strong>, Java or <strong><a href=\"https:\/\/liora.io\/en\/sql-learn-all-about-the-programming-language-for-databases\">SQL<\/a><\/strong>.&nbsp;\n\nMore globally, the <b>Data Analyst <\/b>must be rigorous, methodical and have significant analytical capabilities. Of course, he must be comfortable with numbers. A Data Analyst is<b> versatile<\/b>.\n\nBe careful, the <strong><a href=\"https:\/\/liora.io\/en\/data-scientist-vs-data-analyst-what-are-the-main-differences\">data analyst differs from the data scientist<\/a><\/strong>. The data scientist is able to <b>process several different data sources<\/b> while the data analyst extracts raw data from a single source. The <b>data scientist<\/b> also has more advanced <b>skills in data visualization<\/b> (data visualization). He also has <b>machine learning skills<\/b>.\n<h2>Compensation and outlook<\/h2>\nA <b>data analyst begineer<\/b> can make between $51,000 and $55,000 per year. Otherwise, a Data Analyst makes around <b>$78,676 per year<\/b> according to Burning Glass, <b>$75,022<\/b> according to Indeed, and <b>$61,122<\/b> according to PayScale.&nbsp;\n\nYou should know the salary <b>depends on the company<\/b> in which you work and especially your<b> level of skills<\/b>. The data analyst has strong evolutionary prospects. It can become a data scientist by training in data visualization and <strong><a href=\"https:\/\/liora.io\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\">machine learning<\/a><\/strong>. He can also become a <strong><a href=\"https:\/\/liora.io\/en\/how-to-become-a-data-engineer\">data engineer<\/a><\/strong> after several years of experience. If you like management, it is also possible to go to the professions of <b>Data security manager<\/b>, <b>Chief Data Officer<\/b> or <b>Master Data Officer<\/b>.\n<h3>Vacancies for a Data Analyst<\/h3>\nThe professional integration for a data analyst is excellent and the <b>remuneration very attractive<\/b>. Data analyst offers are flooding the labor market. The Big Data businesses are now considered to be <b>future-oriented<\/b>, secure and fast-growing. As for Linkedin, more than <b>2,000 offers have been published this summer alone<\/b>. Chanel, Dior, Ikea, Amazon, Goldman and Sachs or BNP Paribas, all companies without exception are <b>looking for data analysts<\/b>. Whether you want to work in a small or large structure, in finance or luxury, you will find your happiness.\n<h3>What are the advantages to work in Data Science ?<\/h3>\nBeyond job security, the job of Data Analyst has the advantage of a <b>good work\/life balance<\/b>. In addition, most interviewees feel that they have a good working environment and are fulfilled at work. If you have a real <b>appetite for coding and statistics<\/b>, this job is for you.\n\nThe offers are also very varied. Whether you are a young student looking for an apprenticeship contract, looking for an internship or a permanent contract, companies offer <b>all kinds of offers<\/b>.\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex is-content-justification-center\"><div class=\"wp-block-button \"><a class=\"wp-block-button__link wp-element-button \" href=\"\/en\/courses\/data-ai\/data-analyst\">Discover the Data Analyst training<\/a><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>With the advent of e-commerce and social networks, massive amounts of data have emerged. This is called Big Data. All this information has become crucial for companies to analyze competition, get feedback on their products\/services and attract customers. To manage and collect these astronomical amounts of data, companies use data analysts and data scientists. They [&hellip;]<\/p>\n","protected":false},"author":80,"featured_media":207692,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"_acf_changed":false,"editor_notices":[],"footnotes":""},"categories":[2433],"class_list":["post-165613","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/165613","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/users\/80"}],"replies":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/comments?post=165613"}],"version-history":[{"count":3,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/165613\/revisions"}],"predecessor-version":[{"id":207693,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/165613\/revisions\/207693"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media\/207692"}],"wp:attachment":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media?parent=165613"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/categories?post=165613"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}